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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing. >Imaging Small PEC Spheres by a Linear $delta$ Approach
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Imaging Small PEC Spheres by a Linear $delta$ Approach

机译：通过线性$ delta $方法对小型PEC球进行成像

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摘要

The problem of localizing small inhomogeneities from the knowledge of their scattered field is dealt with. In particular, the case of small perfect electric conducting spheres is of concern, with the scattered field data collected under multistatic/multifrequency/single-view or multistatic/single-frequency/multiview far zone configurations. The multiple scattering between the spheres is neglected, and their locations are represented as the supports of the Dirac delta functions. This allows one to cast the problem as the inversion of a linear integral operator, with the delta functions being the unknowns of the problem. The inversion of this linear integral operator is achieved by means of the truncated singular value decomposition. The performance of the linear inversion algorithm against the model error (i.e., for situations where the multiple scattering is not negligible) is investigated by numerical simulations. Furthermore, the effect of noise is also analyzed by corrupting the data by an uncorrelated additive white Gaussian process.
机译：解决了从小不均匀性的分散域知识中定位局部问题。特别地，小的理想导电球体的情况是值得关注的，在多静态/多频率/单视图或多静态/单频率/多视图远区配置下收集的散射场数据。球之间的多重散射被忽略，它们的位置被表示为狄拉克δ函数的支持。这样就可以将问题转换为线性积分算子的反演，而增量函数就是问题的未知数。该线性积分算子的求逆通过截断的奇异值分解实现。通过数值模拟研究了线性反演算法针对模型误差的性能（即对于多重散射不可忽略的情况）。此外，还通过不相关的加性高斯白化过程破坏数据来分析噪声的影响。

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